An Apriori-Based Knowledge Mining Method for Product Configuration Design

Li Yu; Yun Chen

doi:10.4028/www.scientific.net/AMR.139-141.1490

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 139-141An Apriori-Based Knowledge Mining Method for...

An Apriori-Based Knowledge Mining Method for Product Configuration Design

Abstract:

Product configuration design is a knowledge intensive process during product development. It is a critical step as the cost and quality of a product is based on decisions made at this stage. In the iterative process of product configuration design, customers and design engineers use different terms describing products which often results in misunderstanding. Based on the historical transaction records of customer requirements and design parameters, this paper proposes an Apriori-based data mining method to transform the implicit knowledge into explicit association rules. Three criterions, support, confidence and interestingness, are applied for the evaluation of the extracted rules. The effectiveness of the proposed method is illustrated with a case study of electrical bicycles. The results show that that the proposed method can be a promising tool for product configuration design.

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Periodical:

Advanced Materials Research (Volumes 139-141)

Pages:

1490-1493

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.139-141.1490

Citation:

Cite this paper

Online since:

October 2010

Authors:

Li Yu, Yun Chen

Keywords:

Apriori, Association Rule, Data Mining (DM), Product Configuration Design

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References

[1] W. Lv, F. Lin, J. Ren and S. Lv: Proc. Information Systems and Signal Processing, Proceedings of the SPIE (Chongqing, China, September 20-23, 2005). Vol. 6041, pp.1-5.

Google Scholar

[2] J. Jiao and M. Tseng: Proc. The 3rd Interdisciplinary World Congress on Mass Customization and Personalization (Hong Kong, China, September 18-21, 2005). Session H2-#144, pp.1-10.

Google Scholar

[3] Y. Huang, H. Liu, W. Ng, W. Lu, B. Song and X. Li: Journal of Manufacturing Technology Management, Vol. 19 (2008) No. 6, pp.744-754.

Google Scholar

[4] J. Jiao and Y. Zhang: Computer Aided Design, Vol. 37 (2005) No. 2, pp.149-172.

Google Scholar

[5] L. Yu and L. Wang: Accepted by Journal of Intelligent Manufacturing (2009), DOI 10. 1007/s10845-009-0255-0.

Google Scholar

[6] X. -Y. Shao, Z. -H. Wang, P. -G. Li and C. -X. J. Feng: International Journal of Production Research, Vol. 44 (2006) 14, pp.2789-2811.

Google Scholar

[7] R. Agrawal and R. Srikant: Proc. The 20th International Conference on Very Large Databases (Santiago, Chile, September 12-15, 1994). pp.487-499.

Google Scholar